diff options
Diffstat (limited to 'src/backends/cl')
3 files changed, 4 insertions, 24 deletions
diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp index 3b6aa6cd7c..e8af0ee3b7 100644 --- a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp +++ b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp @@ -66,14 +66,6 @@ ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescrip m_KernelTensor = std::make_unique<arm_compute::CLTensor>(); BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout); - arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX, - m_Data.m_Parameters.m_StrideY, - m_Data.m_Parameters.m_PadLeft, - m_Data.m_Parameters.m_PadRight, - m_Data.m_Parameters.m_PadTop, - m_Data.m_Parameters.m_PadBottom, - arm_compute::DimensionRoundingType::FLOOR); - const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(m_Data.m_Parameters.m_DilationX, m_Data.m_Parameters.m_DilationY); @@ -92,6 +84,8 @@ ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescrip input.info()->set_data_layout(aclDataLayout); output.info()->set_data_layout(aclDataLayout); + arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters); + m_ConvolutionLayer.configure(&input, m_KernelTensor.get(), m_BiasTensor.get(), diff --git a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp index e681e95d90..126950c348 100644 --- a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp +++ b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp @@ -91,14 +91,6 @@ ClDepthwiseConvolutionWorkload::ClDepthwiseConvolutionWorkload( BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); } - const arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX, - m_Data.m_Parameters.m_StrideY, - m_Data.m_Parameters.m_PadLeft, - m_Data.m_Parameters.m_PadRight, - m_Data.m_Parameters.m_PadTop, - m_Data.m_Parameters.m_PadBottom, - arm_compute::DimensionRoundingType::FLOOR); - const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D( m_Data.m_Parameters.m_DilationX, m_Data.m_Parameters.m_DilationY); @@ -120,6 +112,7 @@ ClDepthwiseConvolutionWorkload::ClDepthwiseConvolutionWorkload( // Get the depth multiplier const unsigned int depthMultiplier = weightInfo.GetShape()[0]; + arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters); // Check for optimisation opportunities. bool use3x3Optimisation = (weightInfo.GetShape()[2] == 3) && (weightInfo.GetShape()[3] == 3); diff --git a/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp index cedfebd33a..7c0736645b 100644 --- a/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp +++ b/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp @@ -65,14 +65,6 @@ ClTransposeConvolution2dWorkload::ClTransposeConvolution2dWorkload( m_WeightsTensor = std::make_unique<arm_compute::CLTensor>(); BuildArmComputeTensor(*m_WeightsTensor, weightInfo, m_Data.m_Parameters.m_DataLayout); - arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX, - m_Data.m_Parameters.m_StrideY, - m_Data.m_Parameters.m_PadLeft, - m_Data.m_Parameters.m_PadRight, - m_Data.m_Parameters.m_PadTop, - m_Data.m_Parameters.m_PadBottom, - arm_compute::DimensionRoundingType::FLOOR); - if (m_Data.m_Parameters.m_BiasEnabled) { m_BiasesTensor = std::make_unique<arm_compute::CLTensor>(); @@ -89,6 +81,7 @@ ClTransposeConvolution2dWorkload::ClTransposeConvolution2dWorkload( input.info()->set_data_layout(aclDataLayout); output.info()->set_data_layout(aclDataLayout); + arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters); m_Layer.configure(&input, m_WeightsTensor.get(), m_BiasesTensor.get(), &output, padStrideInfo); InitializeArmComputeClTensorData(*m_WeightsTensor, m_Data.m_Weight); |